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ContactGrasp: Functional Multi-finger Grasp Synthesis from Contact

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abstract

Grasping and manipulating objects is an important human skill. Since most objects are designed to be manipulated by human hands, anthropomorphic hands can enable richer human-robot interaction. Desirable grasps are not only stable, but also functional: they enable post-grasp actions with the object. However, functional grasp synthesis for high degree-of-freedom anthropomorphic hands from object shape alone is challenging because of the large optimization space. We present ContactGrasp, a framework for functional grasp synthesis from object shape and contact on the object surface. Contact can be manually specified or obtained through demonstrations. Our contact representation is object-centric and allows functional grasp synthesis even for hand models different than the one used for demonstration. Using a dataset of contact demonstrations from humans grasping diverse household objects, we synthesize functional grasps for three hand models and two functional intents. The project webpage is https://contactdb.cc.gatech.edu/contactgrasp.html.

fields

cs.CV 1

years

2019 1

verdicts

UNVERDICTED 1

representative citing papers

Towards Markerless Grasp Capture

cs.CV · 2019-07-17 · unverdicted · novelty 4.0

The paper proposes a preliminary markerless grasp capture method from video that uses 2D hand pose estimation plus optimization to also model hand-object contact.

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Showing 1 of 1 citing paper.

  • Towards Markerless Grasp Capture cs.CV · 2019-07-17 · unverdicted · none · ref 2 · internal anchor

    The paper proposes a preliminary markerless grasp capture method from video that uses 2D hand pose estimation plus optimization to also model hand-object contact.